In a practical digital signal processing system, a range of outputting a signal is always limited. For example, the largest level range of a 16-bit digital signal is [−32768, 32767]. When an output signal exceeds the range, the amplitude of the signal is limited, that is to say, clipping processing is performed. This highly effective and simple processing method is used in many digital signal processing systems. A clipping phenomenon occurs in voice communication and general audio processing. When a signal is clipped, a large amount of high-frequency harmonics are generated, thus damaging the continuity of a time domain of the signal. The signal discontinuity severely affects auditory experiences, and subjective quality is obviously deteriorated.
In order to improve the subjective quality deterioration caused by clipping, currently, common processing methods generally include cubic spline predication and AR prediction. However, at present, by using these methods, a clipped signal cannot be automatically detected and self-adaptive gain adjustment cannot be performed on the clipped signal, and therefore, essentially improving the subjective quality of the clipped signal is rather difficult. In addition, for clipping restoration methods such as the cubic spline predication and the AR predication, since a signal range may be larger than a range of a signal at an input end or output end during intermediate processing of a system, a range of a restored signal generated by a single clipped signal restoration method may exceed a range of an input or output signal, so that a clipped signal may still be generated when the system is outputting.